This repository offers an implementation of LC-PFN, a method designed for efficient Bayesian learning curve extrapolation.
LC-PFN in action on Google colab and HuggingFace
To set up the Python environment and install the necessary dependencies, follow these steps:
- Create and activate a new Python environment:
conda create -n lcpfn python=3.9
conda activate lcpfn
- Clone the repository and navigate into its directory:
git clone git@github.com:automl/lcpfn.git
cd lcpfn
- Install the required packages:
pip install -r requirements.txt
Try out the notebooks
(require matplotlib
) for training and inference examples.
NOTE: Our model supports only increasing curves with values in
$[0,1]$ . If needed, please consider normalizing your curves to meet these constraints. See an example innotebooks/curve_normalization.ipynb
.
@inproceedings{
adriaensens2023lcpfn,
title={Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks},
author={Adriaensen, Steven and Rakotoarison, Herilalaina and Müller, Samuel and Hutter, Frank},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=xgTV6rmH6n}
}